Virtual reality is an approach to human-machine interaction and environmental visualization in which an “immersive” virtual (or unreal) environment is created to provide a user with the sense of being totally immersed in an artificial, three-dimensional (3D) world that is generated by computer software. A related, more recent approach to human-machine interaction and environmental visualization is augmented reality in which a view of a user's physical, real-world environment may be augmented with virtual elements. Virtual reality and augmented reality are often implemented through the use of display hardware such as head-mounted systems, computer screens and the like. But past approaches to implement virtual and augmented reality through such display devices have met with varied, but suboptimal success.
For example, in the context of energy emissions, many forms of energy emissions are invisible or otherwise undetectable in meaningful ways for human interaction and assessment. As a result, the source of problems related to these emissions may be subsequently difficult to diagnose in real-time during an event. In particular, the energy emissions may be unrecognized or under evaluated as contributing factors to the related problems, thus leaving the problems unsolved. Exemplary problems related to undetected energy emissions may include frequency collisions amongst computing devices in an environment (e.g., frequency collisions between cordless phones in the 2.4 GHz band and microwave signals (particularly poorly shielded microwaves which can emit signals across the 2.4 GHz band), radio frequency identification (RFID) readers (e.g. UHF, operating in the 860 MHz-960 MHz frequencies) and flight-ready aircraft components having potential energy emissions within an effected energy spectrum such as Auxiliary Power Units (APUs)), detecting and correlating physical fatigue (e.g., detecting abhorrent vibrations, frequencies approaching component resonance or harmonics thereof), wireless signal characterization (e.g., investigating areas of weak and strong signal strength/availability), and the like. Traditionally, adequate investigation of similar types of radiation emissions requires an array of equipment, and an arduous and lengthy process, as the presence of radiation itself could not be seen directly, but only extrapolated, based on interpretations of an array of gauge readings and post-processing analysis. The exemplary problems may be more easily identified through improved environmental visualization systems.
In another example, within the context of computing architecture, the process of troubleshooting within a computing architecture system may generally rely on manual evaluations, as a user attempts to understand the process flow of data through the system. In one instance, an employee may be required to trace code, monitor network packets, and the like to ascertain the flow of data throughout a network. As a result, the current methods may be highly cumbersome as there is no way to directly visualize signals traveling through a network, program, or between devices during the troubleshooting process.
Therefore, it may be desirable to have a system and method that improves on existing approaches to environmental visualization.